gprofiler-official
Functional enrichment analysis and more via the g:Profiler toolkit
Decision gist · record as of 2026-08-14
Yes, if you need functional enrichment analysis and the g:Profiler backend remains operational. The low install friction and permissive license are favorable. However, the package is abandoned (last release 2019-04-02) and you should verify that the upstream g:Profiler service itself is still maintained and accessible before committing to a production workflow. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires the g:Profiler backend service to be accessible; no local fallback.
- Optional pandas dependency for DataFrame output.
- Low install friction with a single runtime dependency (requests).
License · maintenance · safety
permissive license (permissive) — Licensed under BSD (permissive), which allows commercial and private use with minimal restrictions.
last release 2019-04-02 (2691 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,384,650 downloads/mo, #3,978 on PyPI
Alternatives
Verify before relying
pip install gprofiler-official
from gprofiler import GProfiler
gp = GProfiler(return_dataframe=True)
results = gp.profile(organism='hsapiens', query=['NR1H4', 'TRIP12', 'UBC'])- Whether the g:Profiler backend service remains operational and maintained independently of this client library.
- Compatibility with current Python 3 versions and whether breaking API changes in 1.0.x remain the only documented incompatibility.
- Whether pandas integration (mentioned as optional) is still functional or requires workarounds.
What it is and what it does
gprofiler-official is the official Python 3 client for the g:Profiler toolkit, a web-based bioinformatics platform for functional analysis. It provides three main tools: g:GOSt (profile) performs enrichment analysis to identify statistically significant functional terms and gene annotations in your query; g:Convert maps gene identifiers between different namespaces (HGNC, Entrez, UniProt, etc.); and g:Orth finds orthologous genes in related organisms. The library communicates with the g:Profiler backend via requests and can optionally return results as pandas DataFrames.
The package is designed for researchers analyzing gene lists from experiments or computational predictions. It abstracts away HTTP communication and result parsing, letting you work directly with Python objects or structured data. The 1.0.x release introduced breaking API changes from the 0.3.x series, so existing code may require migration.
Use it for
- Identify enriched Gene Ontology terms and biological pathways in a list of differentially expressed genes from RNA-seq.
- Convert gene symbols to Entrez Gene IDs or other identifier systems for cross-database lookups.
- Map human genes to their mouse orthologs for translating findings between model organisms.
- Batch-process multiple gene lists with different enrichment parameters and combine results programmatically.
- Integrate functional annotation into automated bioinformatics pipelines without manual web interface interaction.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need functional enrichment analysis and the g:Profiler backend remains operational.
The low install friction and permissive license are favorable. However, the package is abandoned (last release 2019-04-02) and you should verify that the upstream g:Profiler service itself is still maintained and accessible before committing to a production workflow. No known security vulnerabilities.
Install
gprofiler-official on PyPI
Before you install
Low install friction with a single runtime dependency (requests). However, the package is abandoned—last release was 2019-04-02, over 2691 days ago. No recent maintenance or updates are available.
Requires the g:Profiler backend service to be accessible; no local fallback. Optional pandas dependency for DataFrame output.
License in practice
Licensed under BSD (permissive), which allows commercial and private use with minimal restrictions.
Quickstart
pip install gprofiler-official
from gprofiler import GProfiler
gp = GProfiler(return_dataframe=True)
results = gp.profile(organism='hsapiens', query=['NR1H4', 'TRIP12', 'UBC'])Verify before relying
- Whether the g:Profiler backend service remains operational and maintained independently of this client library.
- Compatibility with current Python 3 versions and whether breaking API changes in 1.0.x remain the only documented incompatibility.
- Whether pandas integration (mentioned as optional) is still functional or requires workarounds.
Package facts
| License | permissive license permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagerequests |
| Maintenance | Abandoned 2,691 days since the last release |
| First released | |
| Downloads | 1,384,650 / month, #3,978 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Scientific/Engineering :: Bio-Informatics |
Evidence: gprofiler_official-1.0.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “functional enrichment analysis”
- gprofiler-officialPython interface to g:Profiler toolkit for functional enrichment…
- gseapyPerforms gene set enrichment analysis (GSEA) on genomic data using…
- semantic-link-functions-meteostatAdds semantic functions to FabricDataFrame that automatically enrich…
Give your agent the search over MCP, or paste the wish link into any chat.
More Bio-Informatics packages
NetworkX provides data structures and algorithms for creating, analyzing, and manipulating graphs and networks, supporting everything from simple undirected graphs to complex directed and weighted networks.
Biopython provides Python tools for computational molecular biology, including sequence analysis, structure parsing, database access, and phylogenetic tree manipulation.
However, verify that the custom Biopython License Agreement aligns with your project's licensing requirements before committing to it in production or proprietary work.
Client library for the Firecrawl API that scrapes, crawls, and searches the web, returning clean Markdown or structured data; also indexes research papers from PubMed, bioRxiv, medRxiv, and arXiv.
A self-balancing interval tree data structure that stores and queries overlapping or enveloped ranges, supporting point lookups, range overlaps, and range envelopment queries.
Install it if you need to store and query overlapping or enveloped ranges; the self-balancing design and rich query interface make it significantly easier than…
Albumentations applies image transformations to training data, supporting classification, segmentation, object detection, and pose estimation with a unified API for images, masks, bounding boxes, and keypoints.
Install it if you need a unified, production-grade augmentation API for computer vision tasks.
PubChemPy is a Python wrapper around the PubChem REST API that lets you search for chemical compounds by name, substructure, or similarity, retrieve their properties, and convert between chemical file formats.
Install it if you need programmatic access to PubChem data.
See also gseapy · mygene · pyensembl · gtfparse · bio · biotite · bionty · pyranges · dnaio · biothings-client